1. Field of Invention
The invention relates to an image quality analysis system and method that can assess printed text image quality.
2. Description of Related Art
It is well known that customer satisfaction can be improved and maintenance costs reduced if problems with copiers and printers can be fixed before they become serious enough to warrant a service call by the customer. While current technology exists to enable printers and copiers to call for service automatically when sensors detect certain operating parameters outside of permissible ranges, there is not a very comprehensive manner of detecting incipient system failure or automatically diagnosing when problems with image quality reach a level where human observers perceive a reduction in quality. This is caused not only by the large number of operating parameters that would need to be tracked, but also because these parameters are strongly coupled to one another. That is, a given parameter at a certain value may or may not be a problem depending on the values of other parameters. While existing systems provide some level of image quality analysis, these systems have been found less than satisfactory as image quality determination is machine dependent and may be inconsistent with perceptions of image quality as judged by human users.
Of particular importance in determining overall image quality is resolving problems with printed text quality. The quality of text is one of the most important image quality attributes of a printing system. Being able to analyze these capabilities is essential.
Many printer systems apply special image processing, such as anti-aliasing, to those pieces of images that represent text, while geometric objects such as lines are processed differently and often more simply. The reason for this is that people are visually more sensitive to errors in the rendition of text than of line or similar graphics. Moreover, certain enhancements are meaningful only for text. Thus, in order to optimize processing speed, it is advantageous to apply such enhancement techniques only to fonts.
Text can appear in many formats within a document to be printed. They can be bitmaps, Postscript(copyright) Type 3 fonts, or outline fonts (Postscript(copyright) Type 1 fonts and TrueType fonts). Outline fonts can often obtain the best printed text quality and are by far the most dominant method for representing text in documents today. Thus, a decision by an image processing system of a printer whether to apply enhancement processing is often made based on whether the object is an outline font. In other words, segments of an image that contain bitmap text will typically be processed as other graphical bitmap objects, without text enhancement, such as anti-aliasing, and only outline font segments are subject to text enhancement.
However, because of the complicated geometrical structure of text, it is difficult to perform image quality analysis directly on text characters. While it is possible to measure error between intended and actual shapes of text characters, interpreting the measurement in terms of how a human observer would perceive the error is difficult. Such interpretations have been somewhat unreliable.
A possible solution would be to conduct measurements on simple graphics objects rather than directly on text characters. However, a printer""s image processing may not apply identically to text characters and simple graphics objects. In view of this, results based on such an approach may be misleading. For example, a 400 dpi printer may render lines without anti-aliasing and consequently it would appear from measurements on lines that the printer has severe limitations in terms of accurate line width rendition. Thus, one might expect that such a printer would render text with uneven stroke widths. However, text presented as an outline font may be rendered with anti-aliasing and therefore show nearly perfect apparent stroke width uniformity. Accordingly, in this hypothetical example, it would appear that the printer had an image quality problem when it fact it did not.
In view of this, it would appear that image quality evaluation requires direct evaluation of text. However, due to the complicated geometrical representations of text, such an image quality analysis would not readily be feasible.
There is a need for image output devices, such as printers and copiers, to better self-diagnose problems relating to image quality. Applicants have found that to comprehensively and reliably measure the system performance of a printer or copier, the image quality of the output must be measured.
Systems that can perform image analysis on printed test samples can be used in a variety of ways to provide solutions and value to users of digital printers and copiers, for example as the analysis engine for automatic and/or remote diagnosis of print quality problems, or for monitoring image quality as part of a print quality assurance system. These systems can be used to accurately measure image quality of printed text.
One exemplary embodiment of the systems and methods of the invention overcomes such problems by developing powerful diagnosing tools within a digital printer or copier for self-diagnosis and evaluation of image quality. Image quality analysis can be performed to monitor many aspects of the printed output of the printing system. Of particular importance to overall image quality is text quality.
In this embodiment, the system provides: one or more digital test patterns stored in memory for providing one or more hard copy output test images; an input scanner that can scan the hard copy test image to form a digital raster image; and an image quality analysis module that receives information about the position of the digital raster image and produces test results relevant to determination of image quality analysis as perceived by human observers, particularly text quality. The input scanner and image quality analysis module may form part of the image output device or may be stand-alone components used to test the device. Optionally, a communication module may be provided that is capable of contacting a service department or a more sophisticated diagnostic module if further analysis or service is necessary, depending on the outcome of the image quality analysis. Alternatively, information relating to text quality may be used by a corrective procedure within the image output device being tested to calibrate the device to correct for detected problems. The image quality analysis and any subsequent corrective procedure should be based on the human visual system (HVS) such that those levels of differences in certain image quality traits that are sufficiently perceived by human observers are considered undesirable image quality degradation. However, even minute differences could be corrected as a preventative measure, even if not visible. A special variation of the human Visual Transfer Function (VTF) may be appropriate to use for text quality, to allow for less than the normal viewing distance (typically 400 mm) to simulate close inspection or the use of a loupe. Factors of human vision, such as the well-known hyperacuity should also be taken into account.
This invention specifically covers one of the many image quality (IQ) metrics that can be part of an overall image quality analysis engine. The specific problem with image quality addressed with this metric is that of printed text.
According to an aspect of the invention, analytical outline fonts are provided that combine the best aspects of graphical objects that are suitable for analytical measurements, while resembling characteristics of real text represented by outline fonts. The key to these analytical characters is that they have less complicated shapes than most real font characters, making it easier to perform image quality analysis.
A series of xe2x80x9canalytical charactersxe2x80x9d are preferably provided, with each being designed to allow easy analytical measurements while providing image quality information useful in assessing particular traits of one or more actual text characters, such as English or Kanji characters in various fonts. Preferably, each analytical font isolates a particular trait.
By making the analytical character in an outline font, the character is processed by the image processing system of the printer as would normal text. As such, its image quality analysis is relevant to image quality analysis of real outline font characters, but without the complicated structure.